runtime-llama 0.10.2

Reduces redundant embedding metadata requests, safely reuses completed exact preparation and fixes interrupted synchronous waits while preserving the existing Python APIs and shared scheduler.

• Admission reuses its just-observed catalog. Frozen owner cohorts and dispatch rounds share fresh metadata without a TTL-based inference permit.
• A bounded adapter-local LRU retains completed exact token IDs, keyed by full prepared text, task/token policy, verified content/semantic identity and tokenizer build/vocabulary. Prepared seals, current limits and fresh model checks remain authoritative. Unknown identity/build bypasses reuse.
• Interrupted blocking waits retire only the affected owner, wake the coordinator and drain actual work before reraising the original exception. Shared POST survivors continue, including through repeated waiter interruptions.
• Incremental queue summaries, iterator packing and constant-time owner rotation avoid repeated growing-prefix scans. A late owner renews partial preflight membership instead of prematurely splitting the tail. The 128-arrival regression now examines 256 records across preview/dispatch instead of 8,256 growing-prefix visits.
• Sync/async APIs, configurable total-text batching, bounded backpressure, deadlines, ordering, identity/topology checks and drained close remain supported by the same scheduler.

Verification: 1,506 retained tests, Ruff check/format, 33 publication packaging tests, normalized wheel/source checks, source/privacy/license audit and a clean isolated public-wheel installation. All 28 runtime payload files match the previously live-qualified candidate byte-for-byte.

The retained 511-text qualification used both already loaded, verified EmbeddingGemma 2 BF16 replicas at unchanged profiles and numerical thresholds: 539 pipeline HTTP requests = 511 exact tokenizations + 4 embedding POSTs + 24 metadata reads, down from 50 metadata reads. All 511 vectors matched the baseline with zero coordinate difference. Separate prepared/raw reuse calls performed zero additional tokenizations after eight initial exact measurements.

Pipeline wall time was 4.6436 s, versus the retained 4.5116 s baseline. No elapsed-time speedup is claimed. These are client/HTTP measurements, not pure GPU timings. Publication adds no new inference benchmark, consumer installation, service restart or model administration.

The lifecycle and evidence are managed with Flower MCP. See the engineering qualification and public release record.

Install the Python wheel below. The three optional tsnet archives retain byte-identical executables and licenses from v0.6.0; this publication adds no new OS execution or VPN enrollment/inference qualification. Apache-2.0 and upstream MIT attribution are unchanged.

RELEASE-MANIFEST.json binds source and asset provenance. Verify downloads using SHA256SUMS. Public wheel SHA-256:

5a98e5c9195c71042fdd7ac62f138a4489e57923346294dafabff6c293e56fcf